Compute Cell-Type-Specific Average Expression of Spatial Clusters

Usage

ComputeAvgs(
  normdata,
  scmeta,
  cluster = "SE",
  Region = NULL,
  scale = TRUE,
  ncores = 4
)

Arguments

normdata: Numeric matrix of normalized expression data, where rows represent genes and columns represent cells.
scmeta: Data frame containing metadata associated with each cell, including spatial cluster and cell type annotations.
cluster: Character string specifying the column name in 'scmeta' containing spatial cluster annotations.
Region: Character string specifying the column name in metadata data frames containing region annotations (default: NULL).
scale: A boolean specifying whether to do univariance normalization.
ncores: Integer specifying the number of CPU cores to use for parallel processing.

Value

A matrix of average expression, where rows represent genes and columns represent spatial clusters from the sample.

Examples

library(data.table)
library(Seurat)
library(SpatialEcoTyper)
library(googledrive)
drive_deauth() # no Google sign-in is required
drive_download(as_id("1CoQmU3u8MoVC8RbLUvTDQmOuJJ703HHB"),
              "HumanMelanomaPatient1_subset_counts.tsv.gz", overwrite = TRUE)
#> File downloaded:
#> • HumanMelanomaPatient1_subset_counts.tsv.gz
#>   <id: 1CoQmU3u8MoVC8RbLUvTDQmOuJJ703HHB>
#> Saved locally as:
#> • HumanMelanomaPatient1_subset_counts.tsv.gz
drive_download(as_id("1nSPj2zRywFUdbo1fwiz77ds4NuM6bmV2"),
              "Melanoma1_subset_SpatialEcoTyper_results.rds", overwrite = TRUE)
#> Error in map(as_id(id), get_one_file_id): ℹ In index: 1.
#> Caused by error in `.f()`:
#> ! Client error: (404) Not Found
#> File not found: 1nSPj2zRywFUdbo1fwiz77ds4NuM6bmV2.
#> • message: File not found: 1nSPj2zRywFUdbo1fwiz77ds4NuM6bmV2.
#> • domain: global
#> • reason: notFound
#> • location: fileId
#> • locationType: parameter
scdata <- fread("HumanMelanomaPatient1_subset_counts.tsv.gz",
                sep = "\t",header = TRUE, data.table = FALSE)
rownames(scdata) <- scdata[, 1]
scdata <- as.matrix(scdata[, -1])
tmpobj <- CreateSeuratObject(scdata) %>%
        SCTransform(clip.range = c(-10, 10), verbose = FALSE)
#> Warning: Data is of class matrix. Coercing to dgCMatrix.
seurat_version = as.integer(gsub("\\..*", "", as.character(packageVersion("SeuratObject"))))
if(seurat_version<5){
  normdata <- GetAssayData(tmpobj, "data")
}else{
  normdata <- tmpobj[["SCT"]]$data
}
metadata = readRDS("Melanoma1_subset_SpatialEcoTyper_results.rds")$metadata

# Construct cell-type-specific gene expression signatures of SEs
avgexprs <- ComputeAvgs(normdata = normdata, scmeta = metadata)
head(avgexprs)
#>                               SE5         SE7         SE0         SE4
#> Fibroblast..PDK4      0.110804267  0.19775972  0.13120621 -0.04927833
#> Fibroblast..TNFRSF17  0.000000000  0.00000000  0.00000000  0.00000000
#> Fibroblast..ICAM3     0.000000000  0.00000000  0.00000000  0.00000000
#> Fibroblast..FAP       0.118792445 -0.13868930  0.05233653  0.03938155
#> Fibroblast..GZMB     -0.031686314 -0.07422975 -0.03297410  0.02567394
#> Fibroblast..TSC2     -0.001888106 -0.03091562 -0.02679740 -0.02925629
#>                              SE6         SE2          SE1         SE3
#> Fibroblast..PDK4     -0.13236092 -0.17959104 -0.025478747  0.01853931
#> Fibroblast..TNFRSF17  0.00000000  0.00000000  0.000000000  0.00000000
#> Fibroblast..ICAM3     0.00000000  0.00000000  0.000000000  0.00000000
#> Fibroblast..FAP       0.05003947 -0.10671133  0.035710822 -0.07657463
#> Fibroblast..GZMB      0.00161892  0.02988412 -0.001820212  0.04700560
#> Fibroblast..TSC2     -0.02869510 -0.05265459  0.117406740  0.13560073